Current imaging systems have many deficiencies in that, one an image is captured, the image is often not pleasing because of exposure, tone scale.
The dynamic range of images captured on one medium (such as negative film) may exceed the dynamic range of the medium that the image is rendered on (such as photographic paper). This results in a loss of image detail in the rendered image. The detail may be lost in the highlight portion of the image (such as when a backlit image is printed light enough to properly render the shadow detail, but rendered too light to show the highlight detail such as the clouds in the sky). Or the detail may be lost in the shadow portion of the image (such as when a “flash-in-the-face” image is rendered properly for the subject of the picture, but the background is rendered too dark to show the detail in the background).
These problems are addressed by the process of exposure adjustment (either adjusting the exposure of the camera for capturing an image, or by adjusting the exposure of a captured image). The exposure of the image is determined such that the lightness of the image's subject is optimally reproduced on the rendered medium. Typical exposure adjustment algorithm use statistics to estimate a correct exposure for an image. This exposure is often not optimal due to the face that the subject of the image is not known.
It is well known that the dynamic range of photographic paper is less than the typical scene dynamic range. The result of this incongruity is that a good deal of scene content is rendered to black or white on the photographic print. For this reason, in an image-processing environment, a tone scale function may be used to reduce the scene dynamic range in order to map more information onto the display medium. There exist many processes for creating a tone scale function on an image dependent basis (e.g., see, U.S. Pat. No. 5,471,987 to Nakazawa et al. (hereinafter “Nakazawa”), incorporated herein by reference). Each of the conventional tone scale function processes examines certain statistical characteristics of the image under consideration in order to automatically generate the tone scale function. In addition, tone scale functions may be generated with manual interactive tools. However, these methods suffer because only the values of image pixels are known. For example, it is difficult to determine whether a dark pixel is the result of only a small amount of exposure to the subject, or because the subject had a low amount of reflectance.